Data Scientist (Marketing)

Description

WeDiscover was founded with the belief that when you combine performance marketing channel experts with data scientists and engineers, amazing things can happen.

We are a young company – founded in early 2020 – and we are growing fast, reaching 36 full-time employees in mid-2024.

Our mission – which has resonated strongly with our diverse and exciting client base – is to build the most innovative and profitable performance marketing campaigns in the world; utilising bespoke & custom-built technology where it can add value.

We are dedicated to creating a technology-centric company where you will be empowered to use your skills to solve difficult problems with innovative and elegant solutions.

And we can prove it! We have recently received a Great Place to Work award, with a 95% happiness score, and have won several industry awards across the years in many categories. See our blog for yourself 🙂

The role:

Joining as a Data Scientist, you will report directly to the Technical Director and work across both internal and external projects. This is an ideal opportunity for someone looking for real ownership and a role to make their own, not to mention the huge prospects for progression that being an early employee will bring.

Given the stage of the company and the broad nature of the role, you’ll have the chance to work with a multitude of languages and software – including Python, SQL, R, AWS & GCP – and will be involved in a varied range of tasks, such as optimization systems, regression modeling, data pipelines, NLP, experimental analysis, and reporting.

You will work within a modern cloud-based data science environment with clearly defined standards and best practices.

Requirements

You should apply if you:

Have a minimum of 2 years of commercial experience in a data science or analyst role.
Are able to demonstrate a basic level of competency with descriptive and inferential statistics and have a solid working knowledge of probability theory and probability distributions.
Understand and can apply Data Science principles to a basic level (such as the scientific method, hypothesis testing and experimental design).
Have a reasonable understanding of more advanced techniques (e.g. regression, optimisation). Experience utilising these in a commercial capacity is a plus.
Are proficient at SQL and have a good understanding of RDB principles and data structures.
Have a working knowledge of Python, R or another programming language commonly used in data science (e.g. Scala).
Have a solid understanding of options for presenting data (graphically and otherwise) and are able to effectively tell stories & derive insights with analysis and reporting.
Have experience and a good working knowledge of digital marketing with experience focussing on projects in the field. Ideally, you would have worked with performance marketing channels (Paid Search, Paid Social, Programmatic etc.) and be well-versed in the fundamental concepts of marketing. You should have an understanding of key performance indicators (KPIs) and the ability to interpret marketing data to support our clients.
Are passionate about creating simple, elegant and scalable data-centric solutions.
Would enjoy working across a varied range of both in-house and client-focussed projects.

Benefits

We truly value your work, time, and skills and in return will offer you a competitive salary and some additional benefits, including:

A salary of £45,000 to £65,000 DOE.
Significant career advancement and learning opportunities.
The opportunity to have a direct impact on the company and our clients.
Top-of-the-range equipment and the freedom to use the right tools and techniques for the job.
The opportunity to gain more experience by mentoring and coaching more, should you wish to.
28 days of holiday (excluding bank holidays).
2 volunteering days a year.
Fully remote working for the foreseeable future.
5 weeks paid sabbatical after 5 years of service.
£40 per month wellness subscription choice (Heights, Calm, Headspace, Huel, Thriva, Gym etc).
£200 Annual learning fund (can be used for books, subscriptions, etc).
Continuous training and development. In both technical and business skills.

Originally posted on Himalayas

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Data Scientist, Data Science Analyst, Marketing Analyst, Marketing Analytics Manager, Data Science Engineer, Data Analyst, Product Insights Data Scientist, Marketing 

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